In this project, I will try to predict race results from a wide variety of predictors for the 2022 Mens World Tour in professional road cycling. Road cycling is notoriously unpredictable so it will be interesting to see how a machine learning algorithm tackles this problem. Predictors will be divided into two general categories. The first category is rider profile. Rider profile includes variables such as rider age, rider weight, and rider ranking in a variety of different strengths. In pro cycling, riders generally specialize. There are riders who are designated sprinters. These riders have a very good 30 second power but are generally larger and do not have good power over longer ranges. This means that these riders are good at sprinting to a win in a flat race but get dropped when there is a hill. There are other riders who are very light and have good long power. These riders are excellent at climbing but cannot compete against the sprinters. There are many riders who specialize somewhere between a sprinter and a climber. The other category of predictor is race profile. This includes attributes such as race length, vertical meters covered, race ranking, and more. Throughout the year, there are certain races that rank higher than other races. For example, most people have heard of the Tour de France but only intense cycling fans know of races such as the Bemer Classic. These higher quality races have better riders starting at them and are thus more prestigious to win raising the level of competition. A rider who could do well at the Bemer Classic might struggle to do well at the Tour de France. By combining rider profile and racer profile, I hope to create an algorithm that is able to provide insights that are missed by most cycling commentators. Since races are so unpredictable, there are many variables that are difficult to quantify and are thus missing from this analysis. For example, there is nothing to quantify what happened in a race known as Strade Bianche in 2022 when strong winds blew half of the competitors off of the course causing some spectacular crashes.
A series of unfortunate events (all riders were relatively ok) Let’s see how the models do.